arrow
返回

A Low Complexity Decoding Scheme for Raptor-Like LDPC Codes

delete2019-12-01
delete3
PRE
AI
Y
Yin Xu
G
Genning Zhang
H
Hao Ju
何
何大治 (Dazhi He) *
孙
孙军 (Jun Sun)
Y
Yiyan Wu
W
Wenjun Zhang
DOI:10.1109/TBC.2019.2921670delete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
Recently, a new structure of low density parity check (LDPC) code named raptor-like LDPC code has attracted much attention. It has better performance at low code rate. In this paper, a novel decoding scheme for raptor-like LDPC code is proposed. First, the Gaussian approximation density evolution (GADE) algorithm is used to track and analyze the message transmission during the decoding process. It is found that certain log likelihood ratio (LLR) messages can be approximated by zero setting in the early iteration of raptor-like LDPC decoding. In other words, some column and row operations could be eliminated without compromise the performance. Next, we propose a new decoding scheme, which can skip unnecessary column and row operations. In comparison with the traditional belief propagation (BP)-based LDPC decoding scheme, the proposed scheme can reduce the decoding complexity. Additionally, a new algorithm is developed to facilitate the selection of the early iteration number. With this novel design, the proposed decoding scheme performs almost the same as the traditional BP-based scheme. To proof the concept, the raptor-like LDPC codes in the ATSC3.0 digital TV system are used to evaluate the proposed scheme, in comparison with the traditional BP-based schemes, i.e., sum-product algorithm (SPA), offset min-sum algorithm (OMSA), and normalized min-sum algorithm (NMSA). The simulation results confirm that the proposed scheme can reduce the decoding complexity without sacrifice in performance for all SPA, OMSA, and NMSA methods. About 10 complexity reduction can be achieved. This will reduce the buttery consumption for Internet of Things (IoT) and handheld devices.
Keyword:
Iterative decoding
Approximation algorithms
Complexity theory
Decoding
Gaussian approximation
Sun
Raptor-like
LDPC
decoding
SPA
OMSA
NMSA
early iteration number
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

IEEE Transactions on Broadcasting 封面图
IEEE Transactions on Broadcasting
IF:
4.8
论文数:
2.1K
被引数:
3.0K

机构

C
Communications Research Centre Canada
学者数:
180
论文数: 235
被引数: 23
S
shanghai jiao tong university
学者数:
15.7W
论文数: 11.7W
被引数: 159
引用论文

引用论文

Offset and Normalized Min-Sum Algorithms for ATSC 3.0 LDPC Decoder
err2017-12-01
err47
PREAI
errMyung, Seho; Park, Sung-Ik; Kim, Kyung-Joong; Lee, Jae-Young; Kwon, Sunhyoung; Kim, Jeongchang
err分享
err收藏
Reduced-complexity decoding of LDPC codesLDPC码的低复杂度译码
err2005-08-01
err785
PREAI
errChen, JH; Dholakia, A; Eleftheriou, E; Fossorier, MRC; Hu, XY
err分享
err收藏
An Overview of the ATSC 3.0 Physical Layer Specification
err2016-03-01
err232
errOAAI
errFay, Luke; Michael, Lachlan; Gomez-Barquero, David; Ammar, Nejib; Caldwell, M. Winston
err分享
err收藏
A Newly Designed Quarter-Rate QC-LDPC Code for the Cloud Transmission System
err2013-03-01
err42
PREAI
errPark, Sung Ik; Kim, Heung Mook; Wu, Yiyan; Kim, Jeongchang
err分享
err收藏
err分享
err收藏
err分享
err收藏
Low-Density Parity-Check Codes for ATSC 3.0
err2016-03-01
err131
PREAI
errKim, Kyung-Joong; Myung, Seho; Park, Sung-Ik; Lee, Jae-Young; Kan, Makiko; Shinohara, Yuji; Shin, Jong-Woong; Kim, Jinwoo
err分享
err收藏
学者 查看更多内容